Researchers create 3D neuron imaging system

The new technique pioneered by researchers from MIT and the University of Vienna has the potential to greatly improve our understanding of neuron behavior (Image: MIT)

A team of researchers from the University of Vienna and MIT have developed a novel way of observing the behavior of neurons on a brain-wide scale. The discovery has potential applications in the medical field, allowing scientists to pinpoint the specific cells involved in a brain disorder, thus aiding them in tailoring a focused course of treatment.

Neurons are specialized cells responsible for taking sensory data, such as sights and smells, encoding the information, and transmuting it into behavior. This is achieved via the sending of electrical impulses, known as action potentials. Previous methods of mapping neurons have involved scanning the brain via laser, targeting specific sample regions. The downside to this technique is that it's very time consuming, making it very difficult to build a unified neural map.

“Looking at the activity of just one neuron in the brain doesn’t tell you how that information is being computed” states Associate Professor of Biological Engineering and Brain and Cognitive Sciences at MIT, Ed Boyden. "For that, you need to know what upstream neurons are doing. And to understand what the activity of a given neuron means, you have to be able to see what downstream neurons are doing.”

In contrast to the current techniques, the novel system for neuron mapping pioneered by Boyden and his researchers has the ability to detect neuron activity to within a millisecond. This is achieved using a method known as light-field imaging which, in its most basic form, allows scientists to measure the angles of absorbed light in order to create a 3D model of the brain and nervous system. The team built on this technique by optimizing one of the light-field telescopes used in this area, modifying the device using tiny lenses to observe many points of the brain at once. This allowed them to observe neuron activity across the entire brain rather than a mere sample, as was the case with previous techniques.

To aid in the detecting of the neurons, the team employed a method that makes neurons themselves easier to detect. This was done by engineering proteins which glow when combined with calcium, which are then picked up by the light-field telescope. The glowing protein is important, as when a neuron transmits a nerve impulse, it causes calcium ions to impact with each other, and this in turn causes the protein to glow. This allows scientists to observe in real time the electrical firing of neurons, building a 3D image on a brain-wide scale.

Initial testing of the 3D mapping technique took the form of tracking neuron activity in the brain of a C elegans worm, a specimen with a very simplistic neural network, chosen because researchers have already traced its entire neural wiring diagram. This allowed the team to observe how the animal reacted to stimuli such as smells in a previously observed neurological system. The researchers have also imaged the brain of a zebrafish larvae, to show that the technique will continue to function when presented with a more neurologically complicated specimen. The larvae's brain boasts roughly 100,000 neurons, firing faster than those in a human brain. Despite the sophistication of the specimen, the team were able to track around 5,000 activated neurons after provoking a response via odor stimuli.

The potential human applications of the new method are myriad, with researchers planning to use the mapping system to observe the behavior of neurons in patients exhibiting a brain disorder. “The ability to survey activity throughout a nervous system may help pinpoint the cells or networks that are involved with a brain disorder, leading to new ideas for therapies” states Boyden.

Looking to the future the team members hope to use a technique known as optogenetics to further hone their research, hopefully allowing them to observe which neurons are playing a role in a specific task. A paper on the team's work is available in the journal Nature Methods.

The following video features Prof. Boyden and graduate student Young-Gyu Yoon explaining the concept behind their work.